Client-side predictive caching for content

ABSTRACT

Disclosed are various embodiments for client-side predictive caching of content to facilitate use of the content. If account is likely to commence use of a content item through a client, the client is configured to predictively cache the content item before the use is commenced. In doing so, the client may obtain an initial portion of the content item from another computing device. The client may then initialize various resources to facilitate use of the content item by the client. The client-side cache may be divided into multiple segments with different content selection criteria.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims priority to,co-pending U.S. Patent Application entitled “CLIENT-SIDE PREDICTIVECACHING FOR CONTENT,” filed on May 9, 2014, and assigned applicationSer. No. 14/274,121, which is incorporated herein by reference in itsentirety.

BACKGROUND

Network-based delivery of media content has largely supplanted otherforms of media content delivery, such as brick-and-mortar video salesand rental stores, mail-based video rental services, and so on. Insteadof traveling a few miles to a physical store or waiting days for a titleto arrive by mail, users may select media content titles to stream totheir devices over high-speed broadband connections. Consequently, usersare quickly growing accustomed to near-immediate delivery of mediacontent. Rising user expectations may lead to frustration when playbackdoes not begin immediately upon user selection of a media content title.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the present disclosure can be better understood withreference to the following drawings. The components in the drawings arenot necessarily to scale, with emphasis instead being placed uponclearly illustrating the principles of the disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1A is a drawing presenting one example of operation of a networkedenvironment according to various embodiments of the present disclosure.

FIG. 1B is a drawing presenting a detailed view of the networkedenvironment of FIG. 1A according to various embodiments of the presentdisclosure.

FIG. 1C is a drawing presenting a view of a networked environment thatfacilitates local cached file exchange according to various embodimentsof the present disclosure.

FIG. 2 is a flowchart illustrating one example of functionalityimplemented as portions of a caching system executed in a client in thenetworked environment of FIG. 1B according to various embodiments of thepresent disclosure.

FIG. 3 is a flowchart illustrating one example of functionalityimplemented as portions of a content access application executed in aclient in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 4 is a flowchart illustrating one example of functionalityimplemented as portions of a content server executed in a computingenvironment in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 5 is a schematic block diagram that provides one exampleillustration of a computing environment employed in the networkedenvironment of FIGS. 1A-1C according to various embodiments of thepresent disclosure.

DETAILED DESCRIPTION

The present disclosure relates to predictive caching for content itemssuch as, for example, movies, television programs, music, video clips,audio clips, applications, and so on. Such content is increasinglyoffered through network streaming or progressive download. If thenetwork connection of the user has bandwidth exceeding the bitrate ofthe content, the content can be played back or otherwise used while itis being downloaded or streamed. Despite having the network bandwidth tosupport streaming, users may still experience delay after initiallyselecting a content item for use. For example, playback may be delayedfor several seconds, leading to user frustration. This delay may be dueto the initial filling of buffers in the client with portions of thecontent item; launching and initializing various software and/orhardware components in the client to perform decryption, decoding, orother functions; or other causes.

Various embodiments of the present disclosure enable instantaneous, ornear instantaneous, playback of network-streamed or progressivelydownloaded content by predictively caching initial portions of contentitems that a user is likely to play back or use. The predictive cachingmay involve downloading initial portions of the content item in advance,downloading metadata including manifest files and decryption keys,decrypting the initial portions of the content items, performingconfiguration tasks, performing initialization tasks, and/or performingother tasks relating to preparing a content item for playback. Variousapproaches to predictive caching are described in U.S. patentapplication Ser. No. 13/592,752 entitled “PREDICTIVE CACHING FORCONTENT” and filed on Aug. 23, 2012, which is incorporated herein byreference in its entirety.

The predictive cache may be maintained and updated according toavailable data storage, available network bandwidth, recommendationsdata, real-time user behavior data, and/or other factors. As will bedescribed, the predictive cache may be divided into multiple segmentscorresponding to multiple data sources for content items that the useris likely to playback or use. For example, the predictive cache mayinclude a reactive segment, a previously accessed segment, a predictivesegment, and/or other segments. The reactive segment may include thosecontent items that can be immediately selected for playback orconsumption within an application in use by the user. The previouslyaccessed segment may include those content items that recently have beenaccessed by the user. The predictive segment may include those contentitems that the user is predicted to access based upon a watch list, userbrowse history, purchase history, rental history, content availabilitydates, behavior of other users, whether the content items are featuredor otherwise specially promoted, whether the user qualifies for free ordiscounted access to the content items, and/or other factors.

With reference to FIG. 1A, shown is one example of operation for anetworked environment 100 a according to various embodiments. Thenetworked environment 100 a includes a computing environment 103 in datacommunication with one or more clients 106 via a network 109. The client106 is rendering a user interface 112 that allows a user to browsecontent items that are available for playback or use. A recommendation115 is rendered in the user interface 112 in this non-limiting example.The recommendation 115 recommends to the user a movie (“World of theGorillas”) that has been predictively cached in the client 106 forinstantaneous playback. The playback is “instantaneous” in the sensethat additional preparation (e.g., obtaining and decrypting contentdata) in the client 106 is not required to begin playback.

The client 106 includes a cache 118 in memory that stores a content iteminitial portion 121 and content item metadata 124 for each predictivelycached content item. Through predictive caching, the client 106 isconfigured to obtain the content item initial portion 121 and thecontent item metadata 124 from the computing environment 103 over thenetwork 109 before the user at the client 106 requests use or playbackof the content item. Further, the client 106 may initialize varioussoftware and/or hardware components based at least in part on thecontent item initial portion 121 and/or the content item metadata 124 inorder to provide an instantaneous use experience when the user selectsthe content item for use.

After the user requests use of the content item, the client 106 may thenbegin to obtain content item subsequent portions 127 in a content stream130 over the network 109 from the computing environment 103. Thus, asthe client 106 exhausts use of the content item initial portion 121, theclient 106 may seamlessly continue use of the content item subsequentportions 127. In the following discussion, a general description of thesystem and its components is provided, followed by a discussion of theoperation of the same.

Turning now to FIG. 1B, shown is a detailed view of the networkedenvironment 100 a according to various embodiments. The networkedenvironment 100 a includes the computing environment 103 in datacommunication with one or more clients 106 via the network 109. Thenetwork 109 includes, for example, the Internet, intranets, extranets,wide area networks (WANs), local area networks (LANs), wired networks,wireless networks, cable networks, satellite networks, or other suitablenetworks, etc., or any combination of two or more such networks.

The computing environment 103 may comprise, for example, a servercomputer or any other system providing computing capability.Alternatively, the computing environment 103 may employ a plurality ofcomputing devices that may be employed that are arranged, for example,in one or more server banks or computer banks or other arrangements.Such computing devices may be located in a single installation or may bedistributed among many different geographical locations. For example,the computing environment 103 may include a plurality of computingdevices that together may comprise a hosted computing resource, a gridcomputing resource, a content delivery network, and/or any otherdistributed computing arrangement. In some cases, the computingenvironment 103 may correspond to an elastic computing resource wherethe allotted capacity of processing, network, storage, or othercomputing-related resources may vary over time.

Various applications and/or other functionality may be executed in thecomputing environment 103 according to various embodiments. Also,various data is stored in a data store 133 that is accessible to thecomputing environment 103. The data store 133 may be representative of aplurality of data stores 133 as can be appreciated. The data stored inthe data store 133, for example, is associated with the operation of thevarious applications and/or functional entities described below.

The components executed in the computing environment 103, for example,include a prediction engine 136, a content server 139, and otherapplications, services, processes, systems, engines, or functionalitynot discussed in detail herein. The prediction engine 136 is executed togenerate a list of content that a user is predicted to use. To this end,the prediction engine 136 may analyze various behavioral data collectedregarding the user along with other data. The list of contentcorresponds to content that the user is likely to playback or consume.The list may include relative priorities for the content correspondingto a relative strength of prediction. The list may be sent to the client106 over the network 109 as prediction data 142.

In one embodiment, the prediction engine 136 may be configured toreceive various caching metrics 143 reported by the clients 106. Forexample, the caching metrics 143 may indicate a proportion of contentitem usage for which client-side processing of cached item metadata hascompleted by the time the user explicitly indicates that use of thecontent item is desired. The caching metrics 143 may indicate aproportion of content item usage for which an initial portion of thecached content has been obtained by the time the user explicitlyindicates that use of the content item is desired. The caching metrics143 may indicate a proportion of content item usage for which thecontent item been determined, or selected, for caching by the time theuser explicitly indicates that the use of the content item is desired.The caching metrics 143 may also report how quickly playback starts,which may indicate how effective the particular cache segments are. Insome cases, the cache metrics 143 may include additional metadata thatindicates why particular content items were selected to be cached, e.g.,which cache segment cached the particular content item. The sizes of thecache segments may also be reported, as well as how long it takes tocache specific content items. The caching metrics 143 may be employed asfeedback to the prediction engine 136 in order to improve futurepredictions according to machine learning techniques.

The content server 139 is executed to serve up content items andassociated data to users of clients 106. To this end, the content server139 is configured to send content data 145 to the client 106 via thenetwork 109. In addition, the content server 139 may generate and senduser interface data to the client 106 to facilitate user browsing,searching, and/or selection of content. Such user interface data maycorrespond to web page data, mobile application data, and/or other formsof user. Such user interface data may include hypertext markup language(HTML), extensible markup language (XML), cascading style sheets (CSS),and/or other data. In one embodiment, the content server 139 may senddirectives to the client 106 that instruct the client 106 topredictively cache preselected content items.

The data stored in the data store 133 includes, for example, useraccount data 148, promotion data 149, popularity data 150, a contentlibrary 151, content similarity data 152, and potentially other data.The content library 151 includes data relating to content items that aremade available by the content server 139 for playback, download,viewing, lease, purchase, etc. Such content items may include, forexample, movies, television shows, music, music videos, video clips,audio clips, applications such as mobile applications, and so on. Thecontent library 151 may include content portions 153, metadata such asmanifests 155 and decryption keys 157, content availabilities 158,and/or other data.

Each of the content portions 153 may correspond to a distinct timesegment of the particular content item. In some cases, multiplealternative content portions 153 may be provided for time segments,e.g., both English and Spanish language audio tracks, different bitrateswith different encoding qualities, and so on. The content portions 153may include Moving Pictures Experts Group (MPEG) video data, H.264 data,Flash® media data, MPEG layer 3 (MP3) audio data, Dolby Digital® audiodata, Advanced Audio Coding (AAC) audio data, data for subtitles, etc.

The manifests 155 may describe, for example, how a particular contentitem is made up of various content portions 153. The manifest 155 mayinclude identifiers for content portions 153 that make up the contentitem along with sequence-specifying data so that the client 106 canobtain and render the content portions 153 in the correct order. Themanifest 155 may also identify various alternative content portions 153for a content item such as, for example, alternative languages,alternative bitrates, and other alternatives. In some cases, themanifest 155 may provide license-related information, including thelocation of the decryption keys 157.

The decryption keys 157 may be employed by the client 106 to decryptcontent portions 153 which are encrypted under digital rights management(DRM) technologies. A decryption key 157 may be sent along with thecontent portions 153 if the client 106 has rights to the correspondingcontent item. The rights to the corresponding content item may expire ata particular time, after a time period, upon a certain number of playsfor the content item, or at some other time. Thus, the decryption keys157 may be configured to expire in response to expiration of the rightsof the client 106 to the corresponding content item. In someembodiments, the decryption keys 157 may be referred to as “licenses”for the corresponding content items.

The content availabilities 158 may indicate dates or times at which thecontent becomes available and/or unavailable. The content availabilities158 may be generally applicable or may apply to certain classes ofusers, classes of consumption (e.g., purchase or rental), or classes ofsubscriptions. Once content is made available, in some cases, thecontent may later be made unavailable. For example, content may be madeavailable for free for users having a certain membership statusbeginning with a starting date. However, the content may be dropped fromthe promotion after an expiration date. The content availabilities 158may be used to indicate new releases, expiring releases, and/or otherclasses of content, which may, in some cases, be of particular interestto users so as to result in adding content to a cache 118 when thecontent meets certain availability criteria. For example, a first usermay express a particular interest in new releases within the past month,while a second user may express a particular interest in content that isto expire from a membership program within the next week.

The promotion data 149 may indicate which content is actively beingpromoted within a content access application, a network site, or othervenue where content is promoted. Whether content is promoted may factorin whether the content is selected to be predictively cached. Forexample, content that is heavily promoted via a gateway page of anetwork site may be more likely to be selected by a user. In somescenarios, the promotions may be associated with a discount or otherincentive that may lead the user to select the content for use.

The popularity data 150 may indicate the relative popularity of contentaccording to various categorizations. For example, the popularity data150 may indicate relative popularity of content with respect to allcontent, relative popularity of content within a specific genre,relative popularity of content among certain demographics orclassifications of users, and so on. A user may be more likely to usepopular content as compared to unpopular content, thus popularity mayfactor into determining whether to predictively cache content items.

The content similarity data 152 may indicate which content is similar toother content. In one embodiment, the content similarity data 152 may begenerated by a collaborative filtering approach based upon consumptionof content by a pool of users or other data sets. Users may be morelikely to consume content that is similar to content they havepreviously consumed or in which they otherwise indicated an interest.

The user account data 148 may include various data associated with useraccounts with the content server 139. Such accounts may be explicitlyregistered and configured by users or may be created implicitly based onclient 106 interaction with the content server 139. The user accountdata 148 may include, for example, behavior history 160, content reviews161, real-time behavior data 162, subscription status 163, bandwidthhistory 164, content preferences 166, watch lists 168, recommended lists170, subaccount data 172, content rights 175, and other data. Inaddition, security credentials, contact information, paymentinstruments, and/or other user-related data may be stored in the useraccount data 148.

The behavior history 160 describes historical behavior of the userassociated with the user account. Such behavior may include a contentconsumption history describing which content items the user has viewed,downloaded, rented, purchased, etc. In one example, the contentconsumption history corresponds to a media consumption historyindicating which media content items the user has viewed, downloaded,rented, purchased, etc. Such behavior may also include a browse historytracking network pages or content the user has previously accessed, asearch history tracking previous search queries, subscription history,purchase and browse history for non-content items, and/or other forms ofonline behavior. As a non-limiting example, a user who views a trailerfor a movie, as recorded in the behavior history 160, may be more likelyto view the movie soon afterward.

The real-time behavior data 162 may include data describing what theuser is currently doing, e.g., what content the user is currentlybrowsing, what search queries the user is currently executing, whatsearch results are being displayed to the user, etc. The real-timebehavior data 162 may be observed by the content server 139 or collectedfrom reports by the client 106. For example, the client 106 may beconfigured to report to the content server 139 that the user is hoveringa cursor over a description of a certain content item in a userinterface. In some embodiments, the real-time behavior data 162 may bemaintained in the client 106 rather than the computing environment 103.

The bandwidth history 164 profiles the network bandwidth available forthe user through the client 106. The bandwidth history 164 may beemployed to select from among multiple bitrates of content itemsautomatically for predictive caching. If the user employs multipleclients 106, multiple profiles may be created in the bandwidth history164. Also, multiple location-dependent profiles may be created forclients 106 that are mobile devices. As a non-limiting example, a usermay have third-generation (3G) cellular data access at an officelocation, but high-speed Wi-Fi data access at a home location, therebyresulting in multiple location-dependent bandwidth profiles for the sameclient 106 in the bandwidth history 164.

The content preferences 166 include various preferences inferred fromuser behavior or explicitly configured by users. Such preferences may berelating to media content quality (e.g., bitrate, codec, etc.), languagepreferences, subtitle preferences, closed captioning preferences,supplemental content preferences (e.g., relating to directors' oractors' commentaries, etc.), parental control preferences, and so on.The watch lists 168 may correspond to lists of content items in whichusers have explicitly indicated that they desire to consume the contentat some time in the future. The recommended lists 170 correspond tolists of content items generated for each user by the prediction engine136.

The subaccount data 172 may be employed to describe preferences orbehaviors that differ across multiple users of a user account. Forinstance, a family may have a single user account but subaccounts foreach member of the family. Each user may explicitly log in to asubaccount, or the subaccount may be inferred based on time of day, dayof the week, identity or type of the client 106, location of the client106, and/or other factors. In some cases, one user may be associatedwith multiple subaccounts. Further, a subaccount may be associated withmultiple users. The subaccount data 172 may specify restrictions oncontent access in some cases. As a non-limiting example, a subaccountfor a child may be limited to access only child-friendly content fromapproved sources. In some cases, different subaccounts may be associatedwith different clients 106.

The content rights 175 may describe the rights to content which areassociated with the user account. For example, a user may have asubscription to certain content or all content available through thecontent server 139. Such a subscription may be for indefinite use,time-limited use, device-limited use, and/or other licensingarrangements. Alternatively, a user may purchase or lease content on aper-content-item basis. The subscription status 163 may indicate thatstatus of the user with respect to content subscriptions, programmemberships, promotions, and/or other statuses that may entitle the userto access certain content or access certain content for no additionalcharge or an otherwise reduced fee.

The content reviews 161 may correspond to user-created ratings and/orreviews of content. For example, the content preferences 166 of a usermay be inferred based upon the types of content that he or she writesfavorable or unfavorable reviews upon. When a user rates content from acertain genre negatively, he or she may be considered less likely toselect content from that genre in the future. However, in some cases,when a user frequently writes reviews or enters ratings for a certaingenre, it may be inferred that the user is likely to select content fromthat genre, regardless of whether the user liked or disliked thecontent.

The client 106 is representative of a plurality of client devices thatmay be coupled to the network 109. The client 106 may comprise, forexample, a processor-based system such as a computer system. Such acomputer system may be embodied in the form of desktop computers, laptopcomputers, personal digital assistants, cellular telephones,smartphones, set-top boxes, music players, web pads, tablet computersystems, game consoles, electronic book readers, or other devices withlike capability. The client 106 may include a display 177. The display177 may comprise, for example, one or more devices such as liquidcrystal display (LCD) displays, electrophoretic ink (E ink) displays,gas plasma-based flat panel displays, organic light emitting diode(OLED) displays, LCD projectors, or other types of display devices, etc.

The client 106 may be configured to execute various applications such asa content access application 179, a caching system 180, and/or otherapplications. The content access application 179 may be executed in theclient 106, for example, to access and render content items from thecomputing environment 103 and/or other servers. Moreover, the contentaccess application 179 may access various other network content servedup by the computing environment 103 and/or other servers, therebyrendering a user interface 112 on the display 177. The content accessapplication 179 may provide various media player functionalityincluding, for example, initiating playback, stopping playback, pausingplayback, adjusting volume, setting preferences, browsing for mediacontent, searching for media content, recommending media content byrendering recommendations 115 (FIG. 1A), and so on. In one embodiment,the content access application 179 comprises a browser application.Where the content corresponds to applications, the content accessapplication 179 may facilitate progressive download and execution ofapplications.

The caching system 180 is executed to predict various content items thatthe user is likely to access and to cache content item initial portions121 (FIG. 1A) and content item metadata 124 (FIG. 1A) in the cache 118to facilitate instantaneous use. The cache 118 may be maintained using aplurality of cache segments. In one embodiment, the cache 118 isstructured to have a reactive segment 181, a previously accessed segment182, a predictive segment 183, and/or other cache segments. The cachesegments may utilize different content selection criteria, as discussedbelow. The different cache segments may also utilize different cacheeviction/purging criteria. In some scenarios, cache segments may be tiedto particular storage devices. For example, one cache segment may be onone storage device, while another cache segment may be on anotherstorage device. In one embodiment, the caching system 180 receivescaching instructions from the computing environment 103 and isconfigured to carry out the caching instructions. In variousembodiments, the prediction engine 136 or portions thereof may beimplemented client-side within the caching system 180.

The reactive segment 181 may include content that is immediatelyselectable for use or playback via a current user interface 112 renderedby the content access application 179. For example, the current userinterface 112 may have buttons, drop-down boxes, links, and/or otheruser interface components that, when selected, initiate usage orplayback of a particular content item. In some cases, content may beselected for the reactive segment 181 when selectable via apredetermined number of actions via the current user interface 112. Forexample, the reactive segment 181 may include all content that isselectable via the current user interface 112 and any user interface 112directly reachable via the current user interface 112. It is understoodthat different user interface 112 screens and portions thereof may beassociated with different reactive caching policies. For example, theproportion of titles reactively cached on a search page may differ fromthe proportion of titles reactively cached on a program season detailpage. A feedback loop may be employed to improve the hit rate of titlescached in the reactive segment 181 over time with respect to thebehavior of users.

The previously accessed segment 182 may include content that the userhas previously used. For example, where the content is a video, the usermay have watched the video in its entirety or may have paused or stoppedthe video at some point before the end. Where the user has paused orstopped the video, the user may likely return at some later time toresume the video. Similarly, even if the user has watched the video inits entirety, the user may return later and review it. Such behavior maybe user dependent; i.e., some users may be more likely to review orresume content, while others may more likely abandon content. In onescenario, where the user has paused or stopped the content at a positionother than at the beginning, the previously accessed segment 182 mayinclude the initial portion of the content corresponding to the positionwhere the content has been paused or stopped.

The predictive segment 183 may include content that the user ispredicted to access based upon a variety of data sources. For example,the caching system 180 may prefetch content corresponding to thatspecified in the prediction data 142. The predictive segment 183 may befilled based upon resource availability and priority of the contentspecified in the prediction data 142. As non-limiting examples, thecontent in the predictive segment 183 may be selected based at least inpart on user account data 148 associated with the user, promotion data149, popularity data 150, content availabilities 158, content similaritydata 152, and/or other data.

In various scenarios, the cache segments of the cache 118 may have fixedor dynamic relative maximum sizes. The sizes may be established based atleast in part on the number of content items (e.g., titles), disk spaceconsumed for the respective content items, user preferences, userbehavior (e.g., for some users a larger reactive cache may be preferred,and so on), and/or other factors. In one scenario, the predictivesegment 183 may be larger than the previously accessed segment 182,which may in turn be larger than the reactive segment 181. However, dueto update frequencies, the contents of the reactive segment 181 may beupdated more frequently than, for example, the predictive segment 183.

The content access application 179 may include various decodingcomponents 184 and decryption components 185 corresponding to logic thatfacilitates usage or playback of content items. The caching system 180may also initialize various decoding components 184, decryptioncomponents 185, etc. for content items in the cache 118. In this regard,various objects may be instantiated in the memory of the client 106 forthe decoding components 184 and the decryption components 185. Theoverall size of the cache 118 may depend, for example, onuser-configured parameters, the available data storage in the client106, the bandwidth available to the client 106 over the network 109, oron other factors. In various embodiments, the client 106 may beconfigured to make predictive caching decisions and/or the computingenvironment 103 may be configured to make predictive caching decisions.

The client 106 may also include a secure data store 187 for storage ofdecryption keys 157 used in decrypting content items to which the userhas rights in the client 106. The secure data store 187 may comply withvarious rules regarding security for storage of DRM licenses. The securedata store 187 may have relatively limited storage space for decryptionkeys 157. In some cases, the limited storage space in the secure datastore 187 may in turn limit the size of the cache 118. The cachingsystem 180 may be configured to install the decryption keys 157 in thesecure data store 187 which the corresponding content items arepredictively cached. The client 106 may be configured to executeapplications beyond the content access application 179 and the cachingsystem 180 such as, for example, browsers, mobile applications, emailapplications, social networking applications, and/or other applications.

Next, a general description of the operation of the various componentsof the networked environment 100 a is provided. To begin, users mayregister and interact with the content server 139 such that behaviorhistory 160 (e.g., consumption history, etc.), bandwidth history 164,content preferences 166, watch lists 168, and/or other data in the useraccount data 148 is created for a content access account. The predictionengine 136 may process this data in order to generate the recommendedlists 170 for the users. In some cases, the recommended lists 170 may bebased on real-time behavior data 162 associated with the users. Suchreal-time behavior data 162 may, for example, describe a listing ofcontent items being presented to the user via a user interface, alisting of search results generated in response to a search queryobtained from the user, content items reachable through navigation pathsvia a user interface, and so on. The recommended lists 170 may dependfurther on the time of day, the day of the week, which subaccount isactive, etc.

As users interact with the content server 139, the popularity data 150and the content similarity data 152 may be generated. In some cases, thepopularity data 150 and the content similarity data 152 may be obtainedfrom other sources. Users may add content to their watch lists 168 andwrite reviews for the content reviews 161. Administrators may configurevarious promotions in the promotion data 149.

The recommended lists 170 and/or other data indicating content that theuser is likely to select may be sent to the client 106 as predictiondata 142. From a list of recommended content items, the caching system180 may select a subset of the list based at least in part on arespective priority of the content items, an available data storage forthe client 106, available storage in the secure data store 187,available bandwidth, power state in the client 106, costs associatedwith the network 109 connection to the client 106, type of network 109connection to the client 106, configuration parameters, and/or otherfactors. In addition, the caching system 180 may determine content itemsto be cached in the reactive segment 181, the previously accessedsegment 182, and/or other cache segments. In one embodiment, the cachingsystem 180 determines the selected subset according to a directive fromthe computing environment 103.

As non-limiting examples, a content item may be selected for cachingbased at least in part on a subscription status 163 of the user andwhether a discounted price for the content item is available for theuser given the subscription status 163, whether the content item willbecome unavailable to the user within a predetermined time periodaccording to the content rights 175 and the content availabilities 158,whether the content item is recommended to the user via a user interface112 of a content access application 179, and/or other factors.

The caching system 180 proceeds to predictively cache the content itemsin the selected subset. In doing so, the caching system 180 may preparethe client 106 for instantaneous use or playback of the selected subsetof content items before the user selects any of the selected subset ofcontent items for use. To this end, the caching system 180 may obtaininitial portions from the content portions 153 and metadata such asmanifests 155 and decryption keys 157 from the content server 139.

The content portions 153 may be sent in an encrypted format. To handlethis, the caching system 180 may obtain decryption keys 157, which arethen installed in the secure data store 187 to handle the decryption.The caching system 180 may spin up and initialize hardware and/orsoftware resources of the client 106, to include, for example, decodingcomponents 184, decryption components 185, and other components of thecontent access application 179. Hardware resources such as displays 117may be configured. Thus, the caching system 180 may perform someprocessing relative to the metadata and/or the initial portion of thecontent item in order to prepare the client 106 for instantaneousplayback of the predictively cached content items prior to the userexplicitly indicating that use or playback is desired.

Instantaneously available use may then be provided by the content accessapplication 179 when any of the selected subset of content items isselected for use or playback by the user. The content access application179 is configured to stream the selected content item from the contentserver 139 as a content stream 130. Although described as“instantaneous” playback, it is understood that such playback mayinclude a fade transition or other transition in order to avoid ajarring experience of cutting directly to playback.

It is understood that the systems of the client 106 described herein maybe employed with a second screen experience. For example, multipledisplays 177 may be utilized, with one display 177 rendering a controluser interface 112 for the content access application 179 and anotherdisplay 177 rendering the actual content. The displays 177 maycorrespond to the same client 106 or multiple clients 106 that are indata communication.

Moving on to FIG. 1C, shown is a drawing presenting a view of anetworked environment 100 b that facilitates local cached file exchange.The networked environment 100 b includes the computing environment 103,a client 106 a, and a client 106 b in data communication via the network109. Although two clients 106 are shown, it is understood that the twoclients 106 are representative of any plurality of clients 106.Additionally, the clients 106 a and 106 b may be in data communicationvia a local network 190. The local network 190 may comprise an Ethernetnetwork, a Wi-Fi® network, a Multimedia over Coax Alliance (MoCA)network, a Bluetooth® network, a Home Phoneline Networking Alliance(HomePNA®) network, and/or other networks that offer relativelyunconstrained bandwidth between local devices.

In the networked environment 100 b, the client 106 a is able to obtaincached data 192 from the client 106 b directly via the local network 190without having to go through the potentially congested network 109 toobtain the data from the computing environment 103. That is to say, thecaching system 180 (FIG. 1B) on the client 106 a is able to obtain thecached data 192 from a cache 118 (FIG. 1B) maintained by the client 106b. In this regard, the client 106 a is able to determine that the cacheddata 192 that is needed is stored by the client 106 b either bycommunicating directly with the client 106 b or by communicating withthe computing environment 103. Discovery-type broadcast messaging may besent across the local network 190 so that each client 106 is aware ofthe state of the other caches 118 existing in clients 106 upon the localnetwork 190. The cached data 192 may comprise content item initialportions 121 (FIG. 1A), content item metadata 124 (FIG. 1A), and/orother data.

Referring next to FIG. 2, shown is a flowchart that provides one exampleof the operation of a portion of the caching system 180 according tovarious embodiments. It is understood that the flowchart of FIG. 2provides merely an example of the many different types of functionalarrangements that may be employed to implement the operation of theportion of the caching system 180 as described herein. As analternative, the flowchart of FIG. 2 may be viewed as depicting anexample method implemented in the client 106 (FIGS. 1A & 1B) accordingto one or more embodiments.

Beginning with box 203, the caching system 180 may obtain predictiondata 142 (FIG. 1B) from the computing environment 103 (FIG. 1B). Theprediction data 142 may indicate a list of content items that the useris at the client 106 is predicted to access. Such prediction data 142may be generated based at least in part on, for example, behaviorhistory 160 (FIG. 1B) including content consumption history, contentpreferences 166 (FIG. 1B), real-time behavior data 162 (FIG. 1B), and/orother data. The list of recommended content items may have a priorityassociated with each content item in the list. Such a priority mayindicate a relative likelihood that the user will want to consume theparticular content item.

In box 206, the caching system 180 determines content items forpredictive caching. Indications of the content items may be added to aqueue for caching in association with respective priorities.Subsequently, the indications of the content items may be selected fromthe queue for caching to be implemented. The selection may be driven bypriority of the respective content items, available resources in theclient 106 (e.g., available memory or data storage allocated for thecache 118 (FIGS. 1A & 1B), available storage in the secure data store187 (FIG. 1B), available bandwidth on the network 109 (FIGS. 1A & 1B)for the client 106, bandwidth history 164 (FIG. 1B), content preferences166 (FIG. 1B), real-time behavior data 162 available to the client 106,configuration parameters, and/or other factors. Where the cache 118 issegmented, the different selection criteria for the segments and therespective capacities of the segments may be considered.

In box 209, the caching system 180 determines whether previously cachedcontent from the cache 118 is to be purged. Such content may be purgedin order to free up resources for other content that is determined to bemore likely to be consumed by the user. The previously cached contentmay also be rendered obsolete by a change to the factors which promptedits initial selection to be predictively cached, e.g., if the content isno longer timely, if the real-time behavior of the user that promptedthe predictive caching of the content has changed, if the user hascompleted consuming the content, and so on. In some cases, the user mayexplicitly request that content be purged from the cache 118. In somecases, the caching system 180 may be able to resize a target cachesegment to accommodate the content item selected for predictive caching.

If previously cached content is to be purged, the caching system 180moves from box 209 to box 212 and determines which of the previouslycached content items are to be purged. In some cases, the user mayexplicitly identify which content is to be purged. In box 215, thecaching system 180 deallocates resources in the client 106 that had beenallocated to the content items that are to be purged. In doing so, thecaching system 180 may, for example, remove content item initialportions 121 (FIG. 1A) from the cache 118, remove content item metadata124 (FIG. 1A) from the cache 118, remove unnecessary decryption keys 157(FIG. 1B) from the secure data store 187, terminate unnecessary decodingcomponents 184 (FIG. 1B) or decryption components 185 (FIG. 1B), and soon. The caching system 180 then proceeds to box 216. If the cachingsystem 180 instead decides not to purge previously cached content, thecaching system 180 moves from box 209 to box 216.

In box 216, the caching system 180 determines the location of thecontent to be cached. In some instances, the content item initialportions 121, the content item metadata 124, and/or other data for thecontent to be cached may be cached by another client 106 upon the localnetwork 190 (FIG. 1C). In other instances, the caching system 180 mayhave to retrieve the data from the computing environment 103. Existingcached content accessible via the local network 190 may be preferred tominimize data usage for the network 109 and/or to improve cachingperformance.

In box 218, the caching system 180 obtains content item initial portions121 from the content server 139 (FIG. 1B) for the content items that areto be predictively cached. The initial portions may correspond to thebeginning of the content item, a location where the user left off inconsuming the content item, a popular location within the content item,and/or other starting portions within the content item. In box 221, thecaching system 180 obtains content item metadata 124 for the contentitems that are to be predictively cached. Such content item metadata 124may include, for example, manifests 155 (FIG. 1B), decryption keys 157,and/or other metadata. In box 224, the caching system 180 initializesvarious components in the client 106 to facilitate instantaneous use orplayback of the predictively cached content items. This may include, forexample, launching and/or initializing decoding components 184 and/ordecryption components 185, storing decryption keys 157 in the securedata store 187, and/or performing other tasks.

In box 227, the caching system 180 may render a user interface 112(FIGS. 1A & 1B) to present recommendations 115 (FIG. 1A) of predictivelycached content items. By recommending such predictively cached contentitems, the likelihood that the user will select content that has beenpredictively cached may be increased, thereby increasing the likelihoodof a positive user experience resulting from instantaneous use. In box230, the caching system 180 may report caching metrics 143 (FIG. 1B) tothe computing environment 103. Thereafter, the portion of the cachingsystem 180 ends.

Turning now to FIG. 3, shown is a flowchart that provides one example ofthe operation of a portion of the content access application 179according to various embodiments. It is understood that the flowchart ofFIG. 3 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content access application 179 as describedherein. As an alternative, the flowchart of FIG. 3 may be viewed asdepicting an example method implemented in the client 106 (FIGS. 1A &1B) according to one or more embodiments.

Beginning with box 303, the content access application 179 obtains arequest to use a content item. For instance, a user may navigate to auser interface 112 (FIGS. 1A & 1B) that presents a content item, and theuser may select a “play” button or other similar user interfacecomponent. In box 306, the content access application 179 determineswhether the content item has been predictively cached in the client 106.If the content item has not been predictively cached in the client 106,or if the predictive caching is incomplete, the content accessapplication 179 may continue to box 309.

In box 309, the content access application 179 obtains a content iteminitial portion 121 (FIG. 1A) from the content server 139 (FIG. 1B).Alternatively, if available, the content access application 179 mayobtain the content item initial portion 121 from another client 106coupled to a local network 190 (FIG. 1C). In box 312, the content accessapplication 179 obtains content item metadata 124 (FIG. 1A) from thecontent server 139. Alternatively, if available, the content accessapplication 179 may obtain the content item metadata 124 from anotherclient 106 coupled to a local network 190 (FIG. 1C). Such content itemmetadata 124 may include, for example, manifests 155 (FIG. 1B),decryption keys 157 (FIG. 1B), and/or other metadata. In box 315, thecontent access application 179 initializes various components in theclient 106 to facilitate use of the content items. This may include, forexample, launching and/or initializing decoding components 184 and/ordecryption components 185, storing decryption keys 157 in the securedata store 187, and/or performing other tasks.

It is noted that performing the tasks of boxes 309-315 may delayplayback of the content item relative to the case in which the contentitem has been predictively cached. The content access application 179then continues to box 318. If the content access application 179determines that the content item has been predictively cached, thecontent access application 179 moves from box 306 to box 318.

In box 318, the content access application 179 begins using the contentitem. If the content item was predictively cached, an instantaneous useexperience is provided as the delay-inducing tasks of boxes 309-315 wereperformed in advance. In box 321, the content access application 179determines whether more data for the content item remains to be streamedor downloaded. If no more data remains, the content access application179 may report caching metrics 143 (FIG. 1B) to the content server 139in box 322 (e.g., caching hits and misses), and the portion of thecontent access application 179 ends. If use is not finished, the contentaccess application 179 instead continues to box 324 and obtains acontent item subsequent portion 127 (FIG. 1A) from the content server139 (or from another client 106, via a local network 190). The contentitem subsequent portion 127 may be identified through processing themanifest 155 for the content item. In box 327, the content accessapplication 179 plays back the content item subsequent portion 127. Thecontent access application 179 then returns to box 321 and determinesagain whether more data remains to be streamed or downloaded.

Moving on to FIG. 4, shown is a flowchart that provides one example ofthe operation of a portion of the content server 139 (FIGS. 1A & 1B)according to various embodiments. It is understood that the flowchart ofFIG. 4 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content server 139 as described herein. As analternative, the flowchart of FIG. 4 may be viewed as depicting anexample method implemented in the computing environment 103 (FIGS. 1A &1B) according to one or more embodiments.

Beginning with box 403, the content server 139 authenticates a user at aclient 106 (FIGS. 1A & 1B). In some cases, the user may be associatedwith a subaccount. The authentication may be performed by a cookie, by ausername/password combination, and/or by another security credential. Inbox 406, the content server 139 provides prediction data 142 (FIG. 1B)to the client 106. In some cases, the content server 139 may providedirectives to the client 106 to predictively cache certain contentitems. In box 409, the content server 139 obtains a request for contentdata 145 (FIG. 1B) from the client 106. The request may be for contentportions 153 (FIG. 1B), manifests 155 (FIG. 1B), decryption keys 157(FIG. 1B), and/or other content data 145.

In box 412, the content server 139 determines whether the client 106 hasrights to the content item to which the content data 145 pertains. Ifnot, the content server 139 may prompt the user to acquire the rights inbox 415. For example, the content server 139 may send data encoding auser interface 112 (FIGS. 1A & 1B) to the client 106, where the userinterface 112 prompts the user to purchase the content item or asubscription. Thereafter, the portion of the content server 139 ends. Insome cases, the encrypted content portions 153 and manifests 155 may besent to the client 106 without the decryption key 157 if the client 106does not have the rights.

If the client 106 does have the rights, the content server 139 movesfrom box 412 to box 418 and sends the content data 145 to the client 106over the network 109 (FIGS. 1A & 1B). In some cases, the content server139 may select from multiple bitrates for the content portions 153,multiple languages in the content portions 153, and/or otheralternatives based on data such as bandwidth history 164 (FIG. 1B),content preferences 166 (FIG. 1B), etc. The bitrate may be adaptivebased at least in part on the currently available bandwidth for theclient 106. In box 421, the content server 139 updates the behaviorhistory 160 (FIG. 1B), the bandwidth history 164 (FIG. 1B), and/or otherdata. In box 424, the content server 139 may obtain caching metrics 143(FIG. 1B) from the client 106. The content server 139 may then recordthe caching metrics 143, which may then be used to improve the operationof the caching system 180 (FIG. 1B) and/or the prediction engine 136(FIG. 1B). Thereafter, the portion of the content server 139 ends.

With reference to FIG. 5, shown is a schematic block diagram of thecomputing environment 103 according to an embodiment of the presentdisclosure. The computing environment 103 includes one or more computingdevices 500. Each computing device 500 includes at least one processorcircuit, for example, having a processor 503 and a memory 506, both ofwhich are coupled to a local interface 509. To this end, each computingdevice 500 may comprise, for example, at least one server computer orlike device. The local interface 509 may comprise, for example, a databus with an accompanying address/control bus or other bus structure ascan be appreciated.

Stored in the memory 506 are both data and several components that areexecutable by the processor 503. In particular, stored in the memory 506and executable by the processor 503 are the prediction engine 136, thecontent server 139, and potentially other applications. Also stored inthe memory 506 may be a data store 133 and other data. In addition, anoperating system may be stored in the memory 506 and executable by theprocessor 503. The client 106 (FIGS. 1A & 1B) may correspond to asimilar computing device 500 having a processor 503 and memory 506.

It is understood that there may be other applications that are stored inthe memory 506 and are executable by the processor 503 as can beappreciated. Where any component discussed herein is implemented in theform of software, any one of a number of programming languages may beemployed such as, for example, C, C++, C#, Objective C, Java®,JavaScript®, Perl, PHP, Visual Basic®, Python®, Ruby, Flash®, or otherprogramming languages.

A number of software components are stored in the memory 506 and areexecutable by the processor 503. In this respect, the term “executable”means a program file that is in a form that can ultimately be run by theprocessor 503.

Examples of executable programs may be, for example, a compiled programthat can be translated into machine code in a format that can be loadedinto a random access portion of the memory 506 and run by the processor503, source code that may be expressed in proper format such as objectcode that is capable of being loaded into a random access portion of thememory 506 and executed by the processor 503, or source code that may beinterpreted by another executable program to generate instructions in arandom access portion of the memory 506 to be executed by the processor503, etc. An executable program may be stored in any portion orcomponent of the memory 506 including, for example, random access memory(RAM), read-only memory (ROM), hard drive, solid-state drive, USB flashdrive, memory card, optical disc such as compact disc (CD) or digitalversatile disc (DVD), floppy disk, magnetic tape, or other memorycomponents.

The memory 506 is defined herein as including both volatile andnonvolatile memory and data storage components. Volatile components arethose that do not retain data values upon loss of power. Nonvolatilecomponents are those that retain data upon a loss of power. Thus, thememory 506 may comprise, for example, random access memory (RAM),read-only memory (ROM), hard disk drives, solid-state drives, USB flashdrives, memory cards accessed via a memory card reader, floppy disksaccessed via an associated floppy disk drive, optical discs accessed viaan optical disc drive, magnetic tapes accessed via an appropriate tapedrive, and/or other memory components, or a combination of any two ormore of these memory components. In addition, the RAM may comprise, forexample, static random access memory (SRAM), dynamic random accessmemory (DRAM), or magnetic random access memory (MRAM) and other suchdevices. The ROM may comprise, for example, a programmable read-onlymemory (PROM), an erasable programmable read-only memory (EPROM), anelectrically erasable programmable read-only memory (EEPROM), or otherlike memory device.

Also, the processor 503 may represent multiple processors 503 and/ormultiple processor cores and the memory 506 may represent multiplememories 506 that operate in parallel processing circuits, respectively.In such a case, the local interface 509 may be an appropriate networkthat facilitates communication between any two of the multipleprocessors 503, between any processor 503 and any of the memories 506,or between any two of the memories 506, etc. The local interface 509 maycomprise additional systems designed to coordinate this communication,including, for example, performing load balancing. The processor 503 maybe of electrical or of some other available construction.

Although the prediction engine 136, the content server 139, the contentaccess application 179 (FIG. 1B), the caching system 180 (FIG. 1B), andother various systems described herein may be embodied in software orcode executed by general purpose hardware as discussed above, as analternative the same may also be embodied in dedicated hardware or acombination of software/general purpose hardware and dedicated hardware.If embodied in dedicated hardware, each can be implemented as a circuitor state machine that employs any one of or a combination of a number oftechnologies. These technologies may include, but are not limited to,discrete logic circuits having logic gates for implementing variouslogic functions upon an application of one or more data signals,application specific integrated circuits (ASICs) having appropriatelogic gates, field-programmable gate arrays (FPGAs), or othercomponents, etc. Such technologies are generally well known by thoseskilled in the art and, consequently, are not described in detailherein.

The flowcharts of FIGS. 2-4 show the functionality and operation of animplementation of portions of the caching system 180, the content accessapplication 179, and the content server 139. If embodied in software,each block may represent a module, segment, or portion of code thatcomprises program instructions to implement the specified logicalfunction(s). The program instructions may be embodied in the form ofsource code that comprises human-readable statements written in aprogramming language or machine code that comprises numericalinstructions recognizable by a suitable execution system such as aprocessor 503 in a computer system or other system. The machine code maybe converted from the source code, etc. If embodied in hardware, eachblock may represent a circuit or a number of interconnected circuits toimplement the specified logical function(s).

Although the flowcharts of FIGS. 2-4 show a specific order of execution,it is understood that the order of execution may differ from that whichis depicted. For example, the order of execution of two or more blocksmay be scrambled relative to the order shown. Also, two or more blocksshown in succession in FIGS. 2-4 may be executed concurrently or withpartial concurrence. Further, in some embodiments, one or more of theblocks shown in FIGS. 2-4 may be skipped or omitted. In addition, anynumber of counters, state variables, warning semaphores, or messagesmight be added to the logical flow described herein, for purposes ofenhanced utility, accounting, performance measurement, or providingtroubleshooting aids, etc. It is understood that all such variations arewithin the scope of the present disclosure.

Also, any logic or application described herein, including theprediction engine 136, the content server 139, the content accessapplication 179, and the caching system 180, that comprises software orcode can be embodied in any non-transitory computer-readable medium foruse by or in connection with an instruction execution system such as,for example, a processor 503 in a computer system or other system. Inthis sense, the logic may comprise, for example, statements includinginstructions and declarations that can be fetched from thecomputer-readable medium and executed by the instruction executionsystem. In the context of the present disclosure, a “computer-readablemedium” can be any medium that can contain, store, or maintain the logicor application described herein for use by or in connection with theinstruction execution system.

The computer-readable medium can comprise any one of many physical mediasuch as, for example, magnetic, optical, or semiconductor media. Morespecific examples of a suitable computer-readable medium would include,but are not limited to, magnetic tapes, magnetic floppy diskettes,magnetic hard drives, memory cards, solid-state drives, USB flashdrives, or optical discs. Also, the computer-readable medium may be arandom access memory (RAM) including, for example, static random accessmemory (SRAM) and dynamic random access memory (DRAM), or magneticrandom access memory (MRAM). In addition, the computer-readable mediummay be a read-only memory (ROM), a programmable read-only memory (PROM),an erasable programmable read-only memory (EPROM), an electricallyerasable programmable read-only memory (EEPROM), or other type of memorydevice.

Further, any logic or application described herein, including theprediction engine 136, the content server 139, the content accessapplication 179, and the caching system 180, may be implemented andstructured in a variety of ways. For example, one or more applicationsdescribed may be implemented as modules or components of a singleapplication. Further, one or more applications described herein may beexecuted in shared or separate computing devices or a combinationthereof. For example, a plurality of the applications described hereinmay execute in the same computing device 500, or in multiple computingdevices in the same computing environment 103. Additionally, it isunderstood that terms such as “application,” “service,” “system,”“engine,” “module,” and so on may be interchangeable and are notintended to be limiting.

Disjunctive language such as the phrase “at least one of X, Y, or Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z).Thus, such disjunctive language is not generally intended to, and shouldnot, imply that certain embodiments require at least one of X, at leastone of Y, or at least one of Z to each be present.

It should be emphasized that the above-described embodiments of thepresent disclosure are merely possible examples of implementations setforth for a clear understanding of the principles of the disclosure.Many variations and modifications may be made to the above-describedembodiment(s) without departing substantially from the spirit andprinciples of the disclosure. All such modifications and variations areintended to be included herein within the scope of this disclosure andprotected by the following claims.

Therefore, the following is claimed:
 1. A system, comprising: acomputing device; and a caching system executable in the computingdevice, wherein when executed the caching system causes the computingdevice to at least: determine a content item to be cached in a clientcache including a plurality of cache segments, wherein the plurality ofcache segments include at least one of: a first cache segment into whichthe content item is selected based at least in part on whether thecontent item is usable in association with an account via a current userinterface rendered by a content access application, a second cachesegment into which the content item is selected based at least in parton whether the content item has been used previously in association withthe account, or a third cache segment into which the content item isselected based at least in part on whether the content item is predictedto be used in association with the account; obtain an initial portion ofthe content item from at least one other computing device prior toreceiving an indication that use of the content item is desired inassociation with the account; obtain metadata associated with thecontent item from at least one other computing device prior to receivingthe indication that the use of the content item is desired inassociation with the account; and prepare the computing device for theuse of the content item prior to receiving the indication that the useof the content item is desired in association with the account, whereinpreparing the computing device for the use of the content item furthercomprises performing processing relative to the metadata.
 2. The systemof claim 1, wherein the plurality of cache segments include at least twoof: the first cache segment, the second cache segment, or the thirdcache segment.
 3. The system of claim 1, wherein when executed thecaching system further causes the computing device to at least report atleast one caching metric to at least one server, the at least onecaching metric indicating at least one of: a respective size forindividual ones of the plurality of cache segments or a respective timeuntil use for the content item.
 4. The system of claim 1, wherein themetadata comprises a corresponding decryption key for the content item.5. The system of claim 1, wherein the metadata comprises a correspondingcontent manifest for the content item.
 6. The system of claim 1, whereinat least two of the plurality of cache segments are associated withcorresponding ones of a plurality of different cache segment capacities.7. A method, comprising: determining, in a first client computingdevice, a content item to be cached in a client cache including aplurality of cache segments, wherein the plurality of cache segmentsinclude at least one of: a first cache segment into which the contentitem is selected based at least in part on whether the content item isusable in association with an account via a current user interfacerendered by a content access application, a second cache segment intowhich the content item is selected based at least in part on whether thecontent item has been used previously in association with the account,or a third cache segment into which the content item is selected basedat least in part on whether the content item is predicted to be used inassociation with the account; and in response to determining the contentitem and before use of the content item via the first client computingdevice: obtaining, in the first client computing device, an initialportion of the content item and metadata associated with the contentitem from a second client computing device; and initializing resourcesof the first client computing device to facilitate use of the contentitem based at least in part on the initial portion of the content item,wherein initializing resources of the first client computing device tofacilitate use of the content item further comprises performingprocessing relative to the metadata.
 8. The method of claim 7, furthercomprising, in response to determining the content item and before theuse of the content item via the first client computing device,obtaining, in the first client computing device, a correspondingmanifest for the content item from the second client computing device.9. The method of claim 7, wherein the first client computing device andthe second client computing device are on a same local network.
 10. Themethod of claim 7, wherein the use of the content item is aninstantaneous use.
 11. The method of claim 7, further comprising:obtaining, in the first client computing device, a correspondingdecryption key from another computing device; and wherein initializingthe resources further comprises initializing a decryption process of thefirst client computing device for decrypting the initial portion of thecontent item using the corresponding decryption key.
 12. The method ofclaim 7, wherein determining the content item is further based at leastin part on a subscription status of the account and whether a discountedprice for the content item is available for the account given thesubscription status.
 13. The method of claim 7, wherein determining thecontent item is further based at least in part on whether the contentitem will become unavailable to the account within a predetermined timeperiod.
 14. The method of claim 7, wherein determining the content itemis further based at least in part on whether the content item willbecome available for access by the account within a predetermined timeperiod.
 15. The method of claim 7, further comprising deallocating, inthe first client computing device, resources associated with apreviously cached content item in response to determining the contentitem to be cached.
 16. The method of claim 7, further comprisingreporting, in the first client computing device, at least one cachingmetric to at least one server, the at least one caching metricindicating at least one of: a first proportion of content item usage forwhich the initial portion of the content item has been obtained when theuser explicitly indicates that the use of the content item is desired;or a second proportion of content item usage for which the content itemhas been determined to be cached when the user explicitly indicates thatthe use of the content item is desired.
 17. The method of claim 7,further comprising: adding, in the first client computing device, thecontent item to a queue in association with a priority; and selecting,in the first client computing device, the content item from the queuebased at least in part on the priority.
 18. A non-transitorycomputer-readable medium embodying a program executable in at least onecomputing device, wherein when executed the program causes the at leastone computing device to at least: determine a content item to be cachedin a client cache including a plurality of cache segments, wherein theplurality of cache segments include at least one of: a first cachesegment into which the content item is selected based at least in parton whether the content item is usable in association with an account viaa current user interface rendered by a content access application, asecond cache segment into which the content item is selected based atleast in part on whether the content item has been used previously inassociation with the account, or a third cache segment into which thecontent item is selected based at least in part on whether the contentitem is predicted to be used in association with the account; obtain aninitial portion of the content item and metadata associated with thecontent item for storage in the client cache prior to receiving anindication that use of the content item is desired in association withthe account; and prepare a particular computing device of the at leastone computing device for the use of the content item prior to receivingthe indication that the use of the content item is desired inassociation with the account, wherein preparing the particular computingdevice for the use of the content item further comprises performingprocessing relative to the metadata.
 19. The non-transitorycomputer-readable medium of claim 18, wherein the metadata comprises amanifest for the content item.
 20. The non-transitory computer-readablemedium of claim 18, wherein the metadata comprises a decryption key fordecrypting the content item.